Motion and Path Planning for Additive Manufacturing
- 1st Edition - November 21, 2023
- Imprint: Elsevier
- Authors: Alex C. Roschli, Michael C. Borish, Abby K. Barnes, Thomas A. Feldhausen, Peter Wang, Eric MacDonald
- Language: English
- Paperback ISBN:9 7 8 - 0 - 4 4 3 - 1 5 2 8 6 - 3
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 1 5 2 8 7 - 0
Motion and Path Planning for Additive Manufacturing takes a deep dive into the concepts and computations behind slicing software – the software that uses 3D models to generate… Read more
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Request a sales quoteMotion and Path Planning for Additive Manufacturing takes a deep dive into the concepts and computations behind slicing software – the software that uses 3D models to generate the commands required to control the motion of a 3D printer and ultimately construct objects.
Starting with a brief review of the different types of motion in additive systems, this book walks through the steps of the path planning process and discusses the different types of toolpaths and their corresponding function in additive manufacturing. Planar, non-planar, and off-axis path planning are examined and explained. This book also presents pathing considerations for different types of 3D-printers, including extrusion, non-extrusion, and hybrid systems as well as 3- and 5-axis systems.
Engineers, researchers, and designers in the additive manufacturing field can use this book as a reference for every step of the path planning process, as well as a guide that explains the computations underlying the creation and use of toolpaths.
- Outlines the entire toolpath planning process required to go from a computer-aided design (CAD) model to G-code that a 3D printer can then use to construct a part
- Defines the terms and variables used in slicing and other path-planning software
- Highlights all the available kinematic arrangements for motion systems in additive manufacturing as well as the advantages and risks of each method
- Discusses the nuances of path planning for extrusion, non-extrusion, and hybrid process as well as 3- and 5-axis additive systems
- Provides an up-to-date explanation of advancements in toolpath planning and state-of-the-art slicing processes that use real-time data collection
Engineers, researchers, and designers in the additive manufacturing field, Undergraduate and graduate students in engineering related fields of study
1. Introduction to AM
2. Kinematics of Motion
3. Motion Platforms
4. Geometry Data Storage
5. Cross-sectioning
6. Closed-Loop Toolpath Generation
7. Space Filling Toolpath Generation
8. Open-Loop Toolpath Generation
9. Support, Raft, Brim, and Skirt Pathing
10. Path Modifiers
11. Travels, Optimizations, and Ordering
12. Pathing Considerations for Extrusion: Pellet, Filament, Concrete and Thermoset
13. Pathing Considerations for DED: Arc Welding and Laser Welding
14. Planar Slicing for Non-Extrusion AM Processes
15. Nonplanar Slicing
16. Pathing Considerations for 5-Axis Planar AM
17. Pathing Considerations for Hybrid AM
18. The G-Code File
19. Closing The Loop
- Edition: 1
- Published: November 21, 2023
- No. of pages (Paperback): 296
- Imprint: Elsevier
- Language: English
- Paperback ISBN: 9780443152863
- eBook ISBN: 9780443152870
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Alex C. Roschli
Alex Roschli obtained a Bachelor's and Master's Degree in Electrical Engineering from the University of Tennessee in 2015 and 2016, respectively. He has conducted research in the Manufacturing Demonstration Facility at Oak Ridge National Laboratory (ORNL) since 2012. His area of expertise and research has centered around the development of large format additive manufacturing and the BAAM (Big Area Additive Manufacturing) system. He has played an integral role in many projects such as 3D printing the first car, a Shelby Cobra, a Guinness World Record holding Boeing 777x wing blade mold, a wind turbine blade mold, and a 34' catamaran boat hull mold.
His current focus is software development for toolpath generation in additive manufacturing. This includes slicing, printing, motor and extrusion control, and closed loop data feedback. Alex manages development of ORNL Slicer 2, a novel toolpath generation software produced at ORNL.
Affiliations and expertise
Oak Ridge National Laboratory, Oak Ridge, USAMB
Michael C. Borish
Dr. Michael Borish is a research staff member in the Manufacturing Demonstration Facility (MDF) at Oak Ridge National Laboratory (ORNL), having joined in 2017. At the MDF, he engages in a wide range of disciplines within Computer Science as they relate to industrial additive manufacturing. This research encompasses visualization, augmented reality, path planning, and computer vision, to name a few. He hopes to expand the boundaries of what we define as manufacturing technology. He is also interested in altering established paradigms of operation particularly as it relates to slicing and path planning and has been developing custom slicing software to that end. He has also built an open-source community around slicing software to advance the state of the art in path planning for industrial additive manufacturing.
Affiliations and expertise
Post-Doctoral Researcher of Computer Science, Oak Ridge National Laboratory, Oak Ridge, USAAB
Abby K. Barnes
Abby Barnes is a Research Communications Professional at Oak Ridge National Laboratory's Manufacturing Demonstration Facility. She was previously a researcher in at the University of Tennessee, Knoxville. She has co-authored two research papers and contributed to five others.
Affiliations and expertise
Research Communications Professional, Oak Ridge National Laboratory's Manufacturing Demonstration Facility, Oak Ridge, USATF
Thomas A. Feldhausen
Thomas Feldhausen is a research staff member and technical lead for hybrid manufacturing at Oak Ridge National Laboratory's Manufacturing Automation and Controls Group. Hybrid manufacturing, a combination of additive and subtractive (machining) manufacturing, is used in his research at ORNL's Manufacturing Demonstration Facility to provide industrial solutions for component repair, tooling and tooling repair, advanced energy systems, aerospace, and automotive applications. Thomas worked at Honeywell Federal Manufacturing in Kansas City before coming to ORNL, where he specialized in multi-axis additive processes for direct ink-write technology.
Affiliations and expertise
Research Staff Member and Technical Lead, Hybrid Manufacturing, Oak Ridge National Laboratory's Manufacturing Automation and Controls Group, Oak Ridge, USAPW
Peter Wang
Peter Wang is a research staff scientist in the Manufacturing Systems Design Group at Oak Ridge National Laboratory (ORNL). Prior to working at ORNL, he worked in aerospace and underground construction industries for 12 years. His previous work experience has covered mechanical and civil structural design, heavy machine design, project management and construction site automation. He obtained his PhD in 2018 from the University of California, Irvine with a focus in robot kinematics. His current research interests cover robotics, manufacturing systems development, automation, additive manufacturing, and the circular economy.
Affiliations and expertise
Researcher, Manufacturing Systems Design Group, Oak Ridge National Laboratory (ORNL), Oak Ridge, USAEM
Eric MacDonald
Eric MacDonald, Ph.D. is Professor of Aerospace and Mechanical Engineering and Murchison Chair at the University of Texas at El Paso, and serves as the Associate Dean of Research and Graduate Studies for the College of Engineering. Dr. MacDonald received his doctoral degree in Electrical and Computer Engineering from the University of Texas at Austin in 2002. He worked in industry for 12 years at IBM and Motorola and subsequently co-founded a start-up specializing in CAD software, which was subsequently acquired by a firm in Silicon Valley. Dr. MacDonald held faculty fellowships at NASA’s Jet Propulsion Laboratory, US Navy Research and was awarded a US State Department Fulbright Fellowship in South America. His research interests include 3D printed multi-functional applications and process monitoring in additive manufacturing with instrumentation and computer vision for improved quality and yield.
Affiliations and expertise
Professor, Aerospace and Mechanical Engineering, The University of Texas at El Paso, Texas, United StatesRead Motion and Path Planning for Additive Manufacturing on ScienceDirect